Data Scientist

new york, New York

A leading global financial services firm is currently seeking a Data Scientist to join their team in New York. This firm is active in investment banking, wealth management, securities, and investment management services.

This firm gives you the opportunity to work next to some of the best professionals in the business with cutting edge technology. The technology team’s priorities include cloud computing, big data and analytics, machine learning, artificial intelligence and cybersecurity as well as staying up to date on emerging technologies.

In this firm not only are you learning and working on prestigious projects but you also have the ability to give back to the community. This firm uses their business skills to help nonprofits and they volunteer globally. This is an excellent opportunity for anyone at any level looking to excel their career.


  • Work with stakeholders, identifying opportunities for leveraging data to solve for business challenges
  • Identify valuable data sources / data sets that can be leveraged to improve results
  • Analyze data to interpret against business opportunity and discover trends and patterns
  • Process, cleanse, and verify the integrity of structured / unstructured data used for analysis
  • Research and implement custom statistical models and machine learning algorithms
  • Execute analytical experiments methodically to evolve an idea into successful solution
  • Coordinate with engineering and software development team to integrate model into continuous business / process / software cycle
  • Present information using data visualization techniques
  • Communicate results and ideas to key stakeholders / decision makers


  • Must have a Master's degree in Computer Science or related field 
  • 7+ years of practical experience as a Data Scientist with proven track record 
  • Strong math skills (e.g. statistics, algebra, multi-variable calculus) 
  • Expertise with R, SQL and Python; familiarity with Scala, Java or C++ is an asset 
  • Extensive background in data mining and statistical analysis 
  • Deep understanding of real-life applicability and limitations of machine-learning algorithms 
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications
  • Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. 
  • Expertise querying Relational / No-SQL databases and using statistical programming languages like R, Python, etc. 
  • Experience with distributed data/computing tools: Hadoop, Hive, Spark, etc. 
  • Experience visualizing/presenting data for stakeholders using: Business Objects, Tableau, D3.js, ggplot, etc. 
  • Experience with data-science tools : Dataiku, Jupyter, etc. 
  • Knowledge of open-source, 3rd party, cloud based data science / NLP / machine learning platforms (e.g. AWS or Azure offerings)
  • Experience with B2B, Financial Industry, Asset Management, Sales & Marketing is highly desired 

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